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[Ibis](https://ibis-project.org) is a portable Python dataframe library, initially created by the same creator of pandas. Today, it's a well-maintained project that supports 20+ backends including pan…
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It would be cool to have Modin for multi-dimensional arrays just like xarray.
Would it be possible to implement this feature or is this just too far from being doable?
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I think it'd be nice to have some transformers that work on dask and numpy arrays, & dask and pandas DataFrames. This would be good since
1. We can depend on dask and pandas, scikit-learn can't
2.…
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Every argument could theoretically be a delayed object, similar to how every argument could be a dask-expr collection, we can't deal with this yet since we never check for them
I created a *very* n…
phofl updated
5 months ago
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Dear outrun dev team,
Just bumped into this awesome tool and I'd like to send kudos to the dev team for implementing it.
I was wondering: would it be imaginable to allow outrun to be used as a Pyt…
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For making spatial joins or overlays, spatial predicates, reading from spatially partitioned datasets, etc more efficient, we can have *spatially partitioned* dataframes: the bounds of each partition …
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**What happened**:
Using RandomizedSearchCV (either from dask-ml or from sklearn with dask's backend) with xgboost (1.2.0 version) the script crushes in most of the runs (sometimes, rather rarely…
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Hi XGBoost!
I am from [Modin](https://github.com/modin-project/modin.git) team. Modin provides an efficient distributed DataFrames and has a [distributed implementation of XGBoost.](https://github.…
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I'm working in a project which involves with querying a Google Bigquery server.
Depending on the sql and the data it's being ran on the output result (table) may be too large to fit in memory.
I…
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I have 25,000 pandas dataframes, each with ~300 columns, each dataframe comprised of just 1 data row with column labels, with ~50% of each dataframe's column labels unique and the other 50% of column …